.
To set up I am going to create the object employeeData0 by using the read function. Because the file I am reading is a csv file, I will use the function read_csv.
#Create object employeeData0
employeeData0=read_csv("https://raw.githubusercontent.com/mahmoudharding/R-You-a-Useful-Model/f1bd9f7558d7f9cf4a63208dc75f11354000a493/datasets/employeeData0.csv")## Parsed with column specification:
## cols(
## ID = col_double(),
## Gender = col_character(),
## `Birth Date` = col_character(),
## Jobcat = col_double(),
## Salary = col_character(),
## `Job Time` = col_double(),
## `Prev Exp` = col_double(),
## Minority = col_double()
## )Next I will create another object, employeeData1, using the read function. This file is a tab delimited file, which means I need to use the function read_tsv.
#Create object employeeData1
employeeData1=read_tsv("https://raw.githubusercontent.com/mahmoudharding/R-You-a-Useful-Model/f1bd9f7558d7f9cf4a63208dc75f11354000a493/datasets/employeeData0.csv")## Parsed with column specification:
## cols(
## `ID,Gender,Birth Date,Jobcat,Salary,Job Time,Prev Exp,Minority` = col_character()
## )Now that both of those are working I will use the code given to me in the assignment to combine the files into a single object.
#Create object allEmployeeData by combing the other two objects
allEmployeeData=rbind(employeeData0,employeeData1)## Error in rbind(deparse.level, ...): numbers of columns of arguments do not matchMaybe if I read employeeData1 as a csv they will match.
#Change employeeData1
employeeData1=read_csv("https://raw.githubusercontent.com/mahmoudharding/R-You-a-Useful-Model/f1bd9f7558d7f9cf4a63208dc75f11354000a493/datasets/employeeData0.csv")## Parsed with column specification:
## cols(
## ID = col_double(),
## Gender = col_character(),
## `Birth Date` = col_character(),
## Jobcat = col_double(),
## Salary = col_character(),
## `Job Time` = col_double(),
## `Prev Exp` = col_double(),
## Minority = col_double()
## )#Create object allEmployeeData by combing the other two objects
allEmployeeData=rbind(employeeData0,employeeData1)That worked. Now I need to create a csv file containing the data from allEmployeeData. I’ll need to use the write_csv function for this, most likely. I’ll call the file “CombinedData.” I’m not sure how the syntax works but I’ll try anyways and see what happens.
#Create a file containing data from allEmployeeData
write_csv(CombinedData,path="allEmployeeData.csv")## Error in is.data.frame(x): object 'CombinedData' not foundI didn’t expect that to work. I put the file name first and then the object, but I think I have it backwards. I think “allEmployeeData” comes first and then I need to create a file name after it.
#Create a file containing data from allEmployeeData
write_csv(allEmployeeData,path="CombinedData.csv")I think that worked. Let’s see if I can read it, just to be sure.
#Attempt to read file CombinedData.csv
read_csv("CombinedData.csv")## Parsed with column specification:
## cols(
## ID = col_double(),
## Gender = col_character(),
## `Birth Date` = col_character(),
## Jobcat = col_double(),
## Salary = col_character(),
## `Job Time` = col_double(),
## `Prev Exp` = col_double(),
## Minority = col_double()
## )## # A tibble: 740 x 8
## ID Gender `Birth Date` Jobcat Salary `Job Time` `Prev Exp` Minority
## <dbl> <chr> <chr> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 1 m 3-Feb-1952 3 $57,000 98 144 0
## 2 2 m 23-May-1958 1 $40,200 98 36 0
## 3 3 f 26-Jul-1929 1 $21,450 98 381 0
## 4 4 f 15-Apr-1947 1 $21,900 98 190 0
## 5 5 m 9-Feb-1955 1 $45,000 98 138 0
## 6 6 m 22-Aug-1958 1 $32,100 98 67 0
## 7 7 m 26-Apr-1956 1 $36,000 98 114 0
## 8 8 f 6-May-1966 1 $21,900 98 0 0
## 9 9 f 23-Jan-1946 1 $27,900 98 115 0
## 10 10 f 13-Feb-1946 1 $24,000 98 244 0
## # ... with 730 more rowsIt worked!!